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OwnerRichard Joseph Mitchellinventor
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A hierarchical constraint enforcement architecture for artificial intelligence systems addresses failures of contractual AI safety governance—including circumvention through provider substitution and erosion through ad-hoc model retraining—by enforcing safety constraints at the deploying entity's own architecture layer, independently of any technology provider. A Constraint Enforcement Layer interposed between an AI processing pipeline and an action execution interface implements three tiers: inviolable constraints cryptographically signed at build time and verified at runtime regardless of provider identity; governance-modifiable constraints subject to authenticated authorization, compatibility validation, and immutable audit records; and operational constraints adjustable within governance-defined bounds. The layer evaluates all proposed actions before execution, maintains deployer-owned persistent state, and persists through provider substitution including government-directed substitution. Applicable across military decision support, clinical AI, large language models, autonomous vehicles, fleet systems, personal assistant operations, executive decision support, regulated communications compliance, patient health advocacy, and governance-as-a-service middleware.
An artificial intelligence constraint enforcement system comprising:
A method for enforcing safety constraints on an artificial intelligence system, the method comprising:
A provider-independent artificial intelligence safety architecture comprising:
Dependencies are inferred from the claim text.